70 lines (69 with data), 1.9 kB

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "summary = pd.read_table('fastqc.txt', sep='\\t')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "summary.set_index('sample_id', inplace=True, drop=False)\n",
    "qc_status = summary.iloc[:, 9:].copy()\n",
    "qc_status.fillna('NA')\n",
    "qc_status = qc_status.astype('str')\n",
    "sample_ids = qc_status.index.values\n",
    "sections = qc_status.columns.values\n",
    "def style_func(val):\n",
    "    status, row, col = val.split('|')\n",
    "    row, col = int(row), int(col)\n",
    "    color = {'pass': 'green', 'fail': 'red', 'warn': 'orange'}.get(status, 'gray')\n",
    "    return '<a href=\"../fastqc/{sample_id}_fastqc.html#M{section}\" style=\"color: {color}\">{status}</a>'.format(\n",
    "        sample_id=sample_ids[row], color=color, status=status, section=col)\n",
    "\n",
    "pd.DataFrame(qc_status.values \\\n",
    "             + '|' + np.arange(qc_status.shape[0]).astype('str')[:, np.newaxis] \\\n",
    "             + '|' + np.arange(qc_status.shape[1]).astype('str')[np.newaxis, :],\n",
    "             index=qc_status.index, columns=qc_status.columns) \\\n",
    "    .style.format(style_func)"
   ]
  }
 ],
 "metadata": {
  "kernel_spec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "laugnage_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "version": "3.6"
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 "nbformat": 4,
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